We extend a unified and easy-to-use approach to measurement error and missing data. In our companion article, Blackwell, Honaker, and King give an intuitive overview of the new technique, along with practical suggestions and empirical applications. Here, we offer more precise technical details, more sophisticated measurement error model…

This study explored the interaction between student characteristics and the online environment in predicting course performance and subsequent college persistence among students in a large urban U.S. university system. Multilevel modeling, propensity score matching, and the KHB decomposition method were used. The most consistent pattern observed…

The redundancy statistic (Rd) is discussed in relation to canonical correlation analysis. The index is a measure of the variance of one set of variables predicted from the linear combination of the other set of variables. A small data set (N=6) from the work of D. Clark (1975) was analyzed using SPSS-X. Two sets of two variables each were…

It is recognized that parametric methods (e.g., t-tests, discriminant analysis, and methods based on analysis of variance) are special cases of canonical correlation analysis. In canonical correlation it has been argued that structure coefficients must be computed to correctly interpret results. It follows that structure coefficients may be useful…

This paper examines some of the problems that arise when conducting multivariate analyses with incomplete data. The literature on the effectiveness of several missing data procedures (MDP) is summarized. The most widely used MDPs are: (1) listwise deletion; (2) pairwise deletion; (3) variable mean; (4) correlational methods. No MDP should be used…

This report investigates the appropriateness of using the General Technical (GT) composite of the Armed Services Vocational Aptitude Battery (ASVAB) as a reenlistment criterion. Three aptitude measures, all ASVAB composites, were compared to measures of proficiency in job performance: the Armed Forces Qualification Test (AFQT), the GT, and the…

This paper discusses the principles underlying discriminant analysis and constructs a simulated data set to illustrate its methods. Discriminant analysis is a multivariate technique for identifying the best combination of variables to maximally discriminate between groups. Discriminant functions are established on existing groups and used to…

Linear classification functions (LCFs) arise in a predictive discriminant analysis for the purpose of classifying experimental units into criterion groups. The relative contribution of the response variables to classification accuracy may be based on LCF-variable correlations for each group. It is proved that, if the raw response measures are…

Although a complex process, canonical correlation has numerous potential advantages over other predictive techniques, the most important being that canonical correlation predicts several criterion variables simultaneously. The paper shows how the method can be used for industrial and vocational-technical education data. (Author)

A two-stage procedure for the analysis of pretest-posttest data was developed and illustrated. Data were reanalyzed from a quasi-experimental evaluation that assessed the effects of an intervention program to teach elementary school children aged 10 to 12 years to watch violence on television more carefully/critically. The treatment group…

Rectifies the unsatisfactory textbook treatment of the finite-sample proprieties of estimators of regression models with a lagged dependent variable and autocorrelated disturbances. Maintains that the bias of the ordinary least squares estimator is determined by the dynamic and correlation effects. (MJP)

This monograph covers the theory, application, and interpretation of both descriptive and inferential statistical techniques in institutional research. Each chapter opens with a hypothetical case study, which is used to illustrate the application of one or more statistical procedures to typical research questions. Chapter 2 covers the comparison…